Philippe Dollfus

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Memristive nanodevices can feature a compact multi-level non-volatile memory function, but are prone to device variability. We propose a novel neural network-based computing paradigm, which exploits their specific physics, and which has virtual immunity to their variability. Memristive devices are used as synapses in a spiking neural network performing(More)
This work proposes two learning architectures based on memristive nanodevices. First, we present an unsupervised architecture that is capable of discerning characteristic features in unlabeled inputs. The memristive nanodevices are used as synapses and learn thanks to simple voltage pulses which implement a simplified "Spike Timing Dependent Plasticity"(More)
The thermoelectric properties of graphene and graphene nanostructures have recently attracted significant attention from the physics and engineering communities. In fundamental physics, the analysis of Seebeck and Nernst effects is very useful in elucidating some details of the electronic band structure of graphene that cannot be probed by conductance(More)
This work discusses the modeling of memristive devices, for architectures where they are used as synapses. It is shown that the most common models used in this context do not always accurately reflect the actual behavior of popular devices in pulse regime. We introduce a new behavioral model, intended towards the nanoarchitecture community. It fits the(More)
This paper discusses the influence of the channel impurity distribution on the transport and the drive current in short-gate MOSFETs. A careful description of electron–ion interaction suitable for the case of discrete impurities has been implemented in a three-dimensional particle Monte Carlo simulator. This transport model is applied to the investigation(More)
Using atomistic quantum simulation based on a tight binding model, we have investigated the transport characteristics of graphene nanomesh-based devices and evaluated the possibilities of observing negative differential conductance. It is shown that by taking advantage of bandgap opening in the graphene nanomesh lattice, a strong negative differential(More)
The Wigner–Boltzmann equation provides the Wigner single particle theory with interactions with bosonic degrees of freedom associated with harmonic oscillators, such as phonons in solids. Quantum evolution is an interplay of two transport modes, corresponding to the common coherent particle-potential processes, or to the decoherence causing scattering due(More)
We present a quantum transport simulation of graphene field-effect transistors based on the self consistent solution of 2D-Poisson solver and Dirac equation within the non-equilibrium Green's function formalism. The device operation of double gate 2D-graphene field effect transistors is investigated. The study emphasizes the band-to-band and Klein tunneling(More)
The thermoelectric properties of in-plane heterostructures made of Graphene and hexagonal boron nitride (BN) have been investigated by means of atomistic simulation. The heterostructures consist in armchair graphene nanoribbons to the sides of which BN flakes are periodically attached. This arrangement generates a strong mismatch of phonon modes between the(More)